# Copyright 2020 The ElasticDL Authors. All rights reserved.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from abc import abstractmethod


class Trainer(object):
    """An abstract trainer to train/evaluate/predict using a minibatch data.
    The trainer will do forward and bachward computation, report gradients
    and update model variables.
    """

    @abstractmethod
    def init_variables_if_need(self, features, labels):
        """Initialize model variables before calling the model"""
        pass

    @abstractmethod
    def train_minibatch(features, labels, train_with_local_model):
        """Train the model using a minibatch data"""
        pass

    @abstractmethod
    def evaluate_minibatch(features, labels):
        """"Evaluate the model using a minibatch data"""
        pass

    @abstractmethod
    def predict_minibatch(features):
        """Model predicts using a minibatch data"""
        pass

    @abstractmethod
    def get_model_version(self):
        """Return the model iteration version"""
        pass

    @abstractmethod
    def get_evaluation_result(self):
        """Return the evaluation result"""
        pass

    @abstractmethod
    def reset_evaluation_result(self):
        """Reset the evaluation result"""
        pass
